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Journal articles on the topic 'Decisions'

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Published: 4 June 2021
Last updated: 29 July 2024

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1

Owens, T. J. "Decision, Decisions, Decisions." Seismological Research Letters 76, no. 2 (March 1, 2005): 177. http://dx.doi.org/10.1785/gssrl.76.2.177-a.

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2

Natal, Gerald, and Barbara Saltzman. "Decisions, decisions, decisions: decision fatigue in academic librarianship." Journal of Academic Librarianship 48, no. 1 (January 2022): 102476. http://dx.doi.org/10.1016/j.acalib.2021.102476.

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3

Causer, Joe, and Paul R. Ford. "“Decisions, decisions, decisions”: transfer and specificity of decision-making skill between sports." Cognitive Processing 15, no. 3 (January 11, 2014): 385–89. http://dx.doi.org/10.1007/s10339-014-0598-0.

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4

Barksdale, Cheryl, and Anne D. Smith. "Decisions, Decisions . . . Resources and Tools for Complex Decision Making." Journal of Management Education 38, no. 6 (August 6, 2014): 894–98. http://dx.doi.org/10.1177/1052562914545226.

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5

Rigopoulos, Evangelos. "DECODING EDUCATIONAL DECISIONS: TRACING THE EVOLUTION OF DECISION-MAKING THEORIES." Global Multidisciplinary Journal 03, no. 03 (March 1, 2024): 01–06. http://dx.doi.org/10.55640/gmj-abc219.

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Decoding Educational Decisions: Tracing the Evolution of Decision-Making Theories explores the historical trajectory and development of decision-making theories within educational contexts. This paper provides a comprehensive examination of the key theories that have shaped decision-making processes in education over time, shedding light on their evolution, implications, and practical applications. Drawing upon a wide range of scholarly literature and historical perspectives, this study offers valuable insights into how decision-making frameworks have influenced educational practices and policies. By tracing the evolution of these theories, educators and policymakers can gain a deeper understanding of the factors influencing decision-making processes in education and make informed choices to enhance teaching, learning, and organizational effectiveness.
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6

Lawson, Stephanie J., Mark R. Gleim, and Michael D. Hartline. "Decisions, decisions: variations in decision-making for access-based consumption." Journal of Marketing Theory and Practice 29, no. 3 (January 10, 2021): 358–74. http://dx.doi.org/10.1080/10696679.2020.1855990.

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7

Smith, Claire, and Soomi Lee. "DECISIONS, DECISIONS: CHARACTERIZING WORKERS' DAILY DECISION PROCESSES DURING LEISURE TIME." Innovation in Aging 6, Supplement_1 (November 1, 2022): 14–15. http://dx.doi.org/10.1093/geroni/igac059.051.

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Abstract Decisions during adulthood set the foundation for healthy aging, but descriptions of healthy and unhealthy decision processes are missing. We extracted latent profiles of daily decision resources (energy and affect) and linked them to daily leisure activity. Diary data was collected from working adults (N=83; Mage=37 years) over the ten workdays (N=693). We identified three daily decision profiles consistent with the Decision Triangle – (1) logical (energetic, unemotional), (2) automatic (less energetic, unemotional), and (3) visceral (unenergetic, highly emotional) – and one additional profile, (4) mild visceral (moderately unenergetic, moderately emotional). Daily logical decision-making related to more “want” leisure activities (i.e., aligned with desires/interests) and the greatest variety in leisure activities. Automatic engaged in the most chores. Visceral engaged in the fewest social activities and least variety in leisure activities. Our findings advance understanding of specific decision processes during leisure, which may have consequences for health and well-being as a person ages.
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8

Bergeron, Caroline D., Daniela B. Friedman, S. Melinda Spencer, Susan C. Miller, DeAnne K. Hilfinger Messias, and Robert McKeever. "An Exploratory Survey of Older Women’s Post-Fall Decisions." Journal of Applied Gerontology 37, no. 9 (July 7, 2016): 1107–32. http://dx.doi.org/10.1177/0733464816653361.

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This research examined factors influencing older women’s post-fall decision making. We surveyed 130 independent older women from continuing care retirement communities and non-institutional homes. We categorized women’s post-fall decisions as medical, corrective, and social decisions, and examined the associations between post-fall decision categories, decisional conflict, number of post-fall changes, self-rated health, frequency of falls, severity of falls, health literacy, awareness and openness to long-term care institutional options, and demographics. Older women experienced greater decisional conflict when making medical decisions versus social ( p = .012) and corrective ( p = .047) decisions. Significant predictors of post-fall decisional conflict were awareness of institutional care options ( p = .001) and health literacy ( p = .001). Future educational interventions should address knowledge deficits and provide resources to enhance collaborative efforts to lower women’s post-fall decisional conflict and increase satisfaction in the decisions they make after a fall.
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9

Doak, Elaine. "Decisions, Decisions, Decisions." Journal of Electronic Resources Librarianship 14, no. 27 (May 29, 2002): 41–51. http://dx.doi.org/10.1300/j101v14n27_06.

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10

Stern, P. "Decisions, decisions, decisions..." Science 344, no. 6186 (May 22, 2014): i—868. http://dx.doi.org/10.1126/science.344.6186.868-i.

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11

Crank, Joe N. "Decisions! Decisions! Decisions!" Academic Therapy 23, no. 5 (May 1988): 515–19. http://dx.doi.org/10.1177/105345128802300512.

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&NA;. "Decisions, decisions, decisions." Nursing Management (Springhouse) 46, no. 2 (February 2015): 6. http://dx.doi.org/10.1097/01.numa.0000460044.86685.f1.

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13

Koretz, Ronald L. "Decisions, decisions, decisions." Gastroenterology 118, no. 6 (June 2000): 1268–69. http://dx.doi.org/10.1016/s0016-5085(00)70381-7.

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14

Lorenzo, Armando J., and Luis H. P. Braga. "Decisions, Decisions, Decisions." Journal of Urology 195, no. 3 (March 2016): 551–53. http://dx.doi.org/10.1016/j.juro.2015.12.055.

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15

Lutter, Lowell D. "Decisions, Decisions, Decisions." Foot & Ankle International 23, no. 3 (March 2002): 195–96. http://dx.doi.org/10.1177/107110070202300301.

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Glimcher, Paul W. "Decisions, Decisions, Decisions." Neuron 36, no. 2 (October 2002): 323–32. http://dx.doi.org/10.1016/s0896-6273(02)00962-5.

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17

Ramsey, Rory, and Kingman P. Strohl. "Decisions, decisions, decisions." Sleep and Breathing 9, no. 4 (November 12, 2005): 143–45. http://dx.doi.org/10.1007/s11325-005-0039-5.

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18

Brown, Robert T., and Lee A. Jackson. "Decisions! Decisions! Decisions!" Journal of School Psychology 28, no. 1 (March 1990): 79–85. http://dx.doi.org/10.1016/0022-4405(90)90037-8.

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19

Hoffman, Saul. "DECISIONS, DECISIONS, DECISIONS." Plastic and Reconstructive Surgery 95, no. 3 (March 1995): 608. http://dx.doi.org/10.1097/00006534-199503000-00054.

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20

Pentecost, Michael J. "Decisions, Decisions, Decisions." Journal of the American College of Radiology 5, no. 10 (October 2008): 1034–35. http://dx.doi.org/10.1016/j.jacr.2008.07.008.

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21

Leykin, Yan, and Robert J. DeRubeis. "Decision-making styles and depressive symptomatology: Development of the Decision Styles Questionnaire." Judgment and Decision Making 5, no. 7 (December 2010): 506–15. http://dx.doi.org/10.1017/s1930297500001674.

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AbstractDifficulty making decisions is one of the symptoms of the depressive illness. Previous research suggests that depressed individuals may make decisions that differ from those made by the non-depressed, and that they use sub-optimal decision-making strategies. For this study we constructed an instrument that aims to measure a variety of decision-making styles as well as the respondent’s view of him or herself as a decision-maker (decisional self-esteem). These styles and estimates of decisional self-esteem were then related to depressive symptoms. Depressive symptomatology correlated negatively with perception of self as a decision-maker. Those with higher depression severity scores characterized themselves as being more anxious about decisions, and more likely to procrastinate. They also reported using fewer productive decision-making strategies, depending more on other people for help with decisions, and relying less on their own intuitions when making decisions. Further research is needed to determine the extent to which these decision-making styles are antecedents to depressive symptomatology or are instead products of, or aspects of, the phenomenology associated with depression.
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22

Scott, Grace, Jacqueline Lam, David Palma, Kevin Fung, and Alexander Louie. "150: Decisions, Decisions - Patient Centred Decision AID for Oropharyngeal Cancer Treatment." Radiotherapy and Oncology 120 (September 2016): S55—S56. http://dx.doi.org/10.1016/s0167-8140(16)33549-6.

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23

Nolte, Julia, and Corinna Löckenhoff. "TO CHOOSE OR NOT TO CHOOSE: CAN AFFECTIVE OR COGNITIVE MECHANISMS EXPLAIN AGE DIFFERENCES IN DECISION AVOIDANCE?" Innovation in Aging 7, Supplement_1 (December 1, 2023): 28–29. http://dx.doi.org/10.1093/geroni/igad104.0094.

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Abstract Older adults are more likely to avoid decisions, which puts them at risk of experiencing negative consumer or health outcomes. Because the underlying reasons remain unclear, this pre-registered online study assessed the roles of (1) affect (especially regret), (2) subjective difficulty, and (3) cognitive ability in explaining age-related differences in decision avoidance. In addition, half of all participants were randomized to a writing intervention aimed at reducing avoidance tendencies. An adult lifespan sample (N = 432, Mage = 50.94, SDage = 19.53 years, 50% women, 62% Non-Hispanic White) chose between making or avoiding four consumer and health-based decisions. Affect, including regret, was assessed before (pre-decisional), during (peri-decisional), and after making decisions (post-decisional). Subjective difficulty was measured during the decision process. Finally, participants completed assessments of demographic background, socio-emotional experience, health, personality, and cognitive ability. We found that older adults were more likely to avoid decisions (p<.001), but age was unrelated to peri-decisional affect and subjective difficulty. Peri-decisional and post-decisional affect were not consistently related to avoidance, but participants who reported more difficulty were more likely to avoid decisions (p=.002). Covariates and cognitive measures could not explain age-related differences, but lower growth-goal-orientation and stronger maximization tendencies predicted decision avoidance after accounting for age (ps<.05). The intervention was successful at improving peri-decisional cognitive load and peri-decisional affect (ps<.05) but did not reduce decision avoidance. In sum, none of the assessed mechanisms could explain age-related increases in decision avoidance. Across age groups, perceived difficulty but not actual cognitive ability predicted avoidance tendencies.
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24

Toi, Alfred Kodjo, Ali Ben Charif, Claudia Lai, Gérard Ngueta, Karine V. Plourde, Dawn Stacey, and France Légaré. "Difficult Decisions for Older Canadians Receiving Home Care, and Why They Are So Difficult: A Web-Based Decisional Needs Assessment." MDM Policy & Practice 7, no. 2 (July 2022): 238146832211240. http://dx.doi.org/10.1177/23814683221124090.

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Background. Older adults receiving home care services often face decisions related to aging, illness, and loss of autonomy. To inform tailored shared decision making interventions, we assessed their decisional needs by asking about the most common difficult decisions, measured associated decisional conflict, and identified factors associated with it. Methods. In March 2020, we conducted a cross-sectional survey with a pan-Canadian Web-based panel of older adults (≥65 y) receiving home care services. For a difficult decision they had faced in the past year, we evaluated clinically significant decisional conflict (CSDC) using the 16-item Decisional Conflict Scale (score 0–100) with a >37.5 cutoff. To identify factors associated with CSDC, we performed descriptive, bivariable, and multivariable analyses using the stepwise selection method with an assumed entry and exit significance level of 0.15 and 0.20, respectively. Final model selection was based on the Bayesian information criterion. Results. Among 460 participants with an average age of 72.5 y, difficult decisions were, in order of frequency, about housing and safety (57.2%), managing health conditions (21.8%), and end-of-life care (8.3%). CSDC was experienced by 14.6% (95% confidence interval [CI]: 11.5%, 18.1%) of respondents on all decision points. Factors associated with CSDC included household size = 1 (OR [95% CI]: 1.81 [0.99, 3.33]; P = 0.27), household size = 3 (2.66 [0.78, 8.98]; P = 0.83), and household size = 4 (6.91 [2.23, 21.39]; P = 0.014); preferred option not matching the decision made (4.05 [2.05, 7.97]; P < 0.001); passive role in decision making (5.13 [1.78, 14.77]; P = 0.002); and lower quality of life (0.70 [0.57, 0.87]; P<0.001). Discussion. Some older adults receiving home care services in Canada experience CSDC when facing difficult decisions. Shared decision-making interventions could mitigate associated factors. Highlights This is the first study in Canada to assess the decisional needs of older adults receiving care at home and to identify their most common difficult decisions. Difficult decisions most frequently made were about housing and safety. The most significant decisional conflict was experienced by people making decisions about palliative care. When their quality-of-life score was low, older adults experienced clinically significant decision conflict.
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Witteman, Holly O., Anne-Sophie Julien, Ruth Ndjaboue, Nicole L. Exe, Valerie C. Kahn, Angela (Angie) Fagerlin, and Brian J. Zikmund-Fisher. "What Helps People Make Values-Congruent Medical Decisions? Eleven Strategies Tested across 6 Studies." Medical Decision Making 40, no. 3 (April 2020): 266–78. http://dx.doi.org/10.1177/0272989x20904955.

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Background. High-quality health decisions are often defined as those that are both evidence informed and values congruent. A values-congruent decision aligns with what matters to those most affected by the decision. Values clarification methods are intended to support values-congruent decisions, but their effects on values congruence are rarely evaluated. Methods. We tested 11 strategies, including the 3 most commonly used values clarification methods, across 6 between-subjects online randomized experiments in demographically diverse US populations ( n1 = 1346, n2 = 456, n3 = 840, n4 = 1178, n5 = 841, n6 = 2033) in the same hypothetical decision. Our primary outcome was values congruence. Decisional conflict was a secondary outcome in studies 3 to 6. Results. Two commonly used values clarification methods (pros and cons, rating scales) reduced decisional conflict but did not encourage values-congruent decisions. Strategies using mathematical models to show participants which option aligned with what mattered to them encouraged values-congruent decisions and reduced decisional conflict when assessed. Limitations. A hypothetical decision was necessary for ethical reasons, as we believed some strategies may harm decision quality. Later studies used more outcomes and covariates. Results may not generalize outside US-based adults with online access. We assumed validity and stability of values during the brief experiments. Conclusions. Failing to explicitly support the process of aligning options with values leads to increased proportions of values-incongruent decisions. Methods representing more than half of values clarification methods commonly in use failed to encourage values-congruent decisions. Methods that use models to explicitly show people how options align with their values offer more promise for helping people make decisions aligned with what matters to them. Decisional conflict, while arguably an important outcome in and of itself, is not an appropriate proxy for values congruence.
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Pereira, Michael, Nathan Faivre, Iñaki Iturrate, Marco Wirthlin, Luana Serafini, Stéphanie Martin, Arnaud Desvachez, Olaf Blanke, Dimitri Van De Ville, and José del R. Millán. "Disentangling the origins of confidence in speeded perceptual judgments through multimodal imaging." Proceedings of the National Academy of Sciences 117, no. 15 (April 1, 2020): 8382–90. http://dx.doi.org/10.1073/pnas.1918335117.

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The human capacity to compute the likelihood that a decision is correct—known as metacognition—has proven difficult to study in isolation as it usually cooccurs with decision making. Here, we isolated postdecisional from decisional contributions to metacognition by analyzing neural correlates of confidence with multimodal imaging. Healthy volunteers reported their confidence in the accuracy of decisions they made or decisions they observed. We found better metacognitive performance for committed vs. observed decisions, indicating that committing to a decision may improve confidence. Relying on concurrent electroencephalography and hemodynamic recordings, we found a common correlate of confidence following committed and observed decisions in the inferior frontal gyrus and a dissociation in the anterior prefrontal cortex and anterior insula. We discuss these results in light of decisional and postdecisional accounts of confidence and propose a computational model of confidence in which metacognitive performance naturally improves when evidence accumulation is constrained upon committing a decision.
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27

Wright, Megan S. "Dementia, Healthcare Decision Making, and Disability Law." Journal of Law, Medicine & Ethics 47, S4 (2019): 25–33. http://dx.doi.org/10.1177/1073110519898040.

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Persons with dementia often prefer to participate in decisions about their health care, but may be prevented from doing so because healthcare decision-making law facilitates use of advance directives or surrogate decision makers for persons with decisional impairments such as dementia. Federal and state disability law provide alternative decision-making models that do not prevent persons with mild to moderate dementia from making their own healthcare decisions at the time the decision needs to be made. In order to better promote autonomy and wellbeing, persons with dementia should be accommodated and supported so they can make their own healthcare decisions.
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Mechitov, Alexander, Helen Moshkovich, and Ronald Klimberg. "VERBAL DECISION ANALYSIS FOR STRATEGIC DECISIONS." International Journal of Business Research 22, no. 1 (March 1, 2022): 26–37. http://dx.doi.org/10.18374/ijbr-22-1.4.

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29

Howard, Ronald A. "Speaking of Decisions: Precise Decision Language." Decision Analysis 1, no. 2 (June 2004): 71–78. http://dx.doi.org/10.1287/deca.1030.0005.

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30

Steele, Katie, Helen M. Regan, Mark Colyvan, and Mark A. Burgman. "Right Decisions or Happy Decision‐makers?" Social Epistemology 21, no. 4 (October 2007): 349–68. http://dx.doi.org/10.1080/02691720601159711.

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31

Horvath, Stephan, and Yung‐Shain Wu. "Voiced/unvoiced decision using sequential decisions." Journal of the Acoustical Society of America 86, no. 6 (December 1989): 2477. http://dx.doi.org/10.1121/1.398400.

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32

Kostbade Hughes, Katherine, and Wendy B. Young. "Decision Making Stability of Clinical Decisions." Nurse Educator 17, no. 3 (May 1992): 12–16. http://dx.doi.org/10.1097/00006223-199205000-00010.

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33

Linkov, Igor, Matthew E. Bates, Benjamin D. Trump, Thomas P. Seager, Mark A. Chappell, and Jeffrey M. Keisler. "For nanotechnology decisions, use decision analysis." Nano Today 8, no. 1 (February 2013): 5–10. http://dx.doi.org/10.1016/j.nantod.2012.10.002.

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34

Youngner, Stuart J., Donald J. Murphy, and Joanne Lynn. "Decision making in support: Sentinel decisions." Journal of Clinical Epidemiology 43 (January 1990): S67—S71. http://dx.doi.org/10.1016/0895-4356(90)90223-c.

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35

Tavakoli, Manouche, Huw TO Davies, and Richard Thomson. "Aiding clinical decisions with decision analysis." Hospital Medicine 60, no. 6 (June 1999): 444–47. http://dx.doi.org/10.12968/hosp.1999.60.6.1139.

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Gonçalves, Vânia. "Decisional Regret in Female Oncofertility Decision Making—An Integrative Narrative Review." Cancers 13, no. 19 (September 22, 2021): 4735. http://dx.doi.org/10.3390/cancers13194735.

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It is well established that fertility is an important issue for young women with cancer at reproductive age, as many have not initiated or completed their parenthood goals when diagnosed. Because cancer treatments may impair fertility, women face fertility decisions that are often complex and surrounded by uncertainty. This may put patients at risk for psychological distress and the experience of regret regarding decisions made at diagnosis, which may be associated with a negative impact on women’s QoL. This narrative review addresses current knowledge about decisional regret regarding fertility preservation decisions in adult female cancer patients at reproductive age. Electronic searches were conducted on Pubmed database for articles published in English from 1 January 2000 to 1 July 2021 that assessed decisional regret following fertility decisions in young women diagnosed at childbearing age. Of the 96 articles identified, nine provided information on decisional regret regarding fertility decisions. Studies reported that, overall, decisional regret regarding oncofertility decisions was low. Factors associated with the experience of decisional regret were patients’ perceived quality and satisfaction with fertility counseling received, the decision to undergo fertility preservation, desire for children and decisional conflict. Health providers should be aware of the factors that are potentially modifiable and prone to improvement in order to reduce decisional regret. All efforts should be made to improve availability of and access to tailored high quality fertility counseling and fertility preservation. Given the growing evidence that decision aids (DAs) are effective in increasing knowledge and reducing decisional conflict and regret, their use in a routine and timely manner to complement fertility counseling is recommended.
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Lord, Kathryn, Gill Livingston, and Claudia Cooper. "A systematic review of barriers and facilitators to and interventions for proxy decision-making by family carers of people with dementia." International Psychogeriatrics 27, no. 8 (April 14, 2015): 1301–12. http://dx.doi.org/10.1017/s1041610215000411.

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ABSTRACTBackground:Relatives of people with dementia report that proxy decision-making is difficult and distressing. We systematically reviewed the literature about barriers and facilitators to family carers of people with dementia making proxy decisions, and interventions used to facilitate their decision-making.Methods:We searched electronic databases and references of included papers up to February 2014. Two authors independently evaluated study quality using a checklist.Results:We included the 30/104 papers from our search which fitted predetermined criteria and prioritized higher quality papers. Family carers report that proxy decision-making is challenging and can be distressing, especially when decisions are made against the wishes of the care recipient and support from healthcare professionals is lacking. Decision-specific manualized aids have been developed, and while results for those supporting decisions about respite and percutaneous endoscopic gastrostomy (PEG) feeding have shown promising results in pilot trials, no intervention has yet been shown to significantly reduce decisional conflict or carer burden, or increase knowledge in randomized controlled trials; a decision aid for advance care planning increased decisional conflict.Conclusions:We recommend development and testing of decision aids targeting the decisions carers report finding most distressing, including those around where people should live, accessing services, and end of life treatments. Being provided with information to make decisions which have not previously been considered may increase feelings of conflict, suggesting these aids should be carefully targeted.
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Hryniv, Sofiia, Elizabeth Gilbride, William Consagra, Supriya Gupta Mohile, Sule Yilmaz, Mary I. Whitehead, Victor G. Vogel, et al. "Exploring decisional control preferences in older patients with cancer and their caregivers." Journal of Clinical Oncology 41, no. 16_suppl (June 1, 2023): 12042. http://dx.doi.org/10.1200/jco.2023.41.16_suppl.12042.

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12042 Background: Shared decision making is preferred by many patients but it is often viewed from the lens of the patient and physician dyad only. Caregivers often support cancer decision-making, although their decision control preferences are not typically considered. We explored decisional control preferences of older patients with cancer and their caregivers, and examined concordance in preferences of the dyad, as well as patient, caregiver, physician factors associated with concordance. Methods: We utilized data from a national geriatric assessment (GA) cluster-randomized trial (NCT 02054741; PI: Mohile; funding NCI UG1CA189961) that recruited patients aged ≥70 with incurable cancer, their caregivers, and oncologists. Controlled Preferences Scale (CPS) was used to assess shared decision making preferences. Both patients and caregivers were asked about the role of patients (Patient-role CPS) and caregiver (Caregiver-role CPS) in the decision making process. Patient-role CPS options were 1) doctor makes the decisions, 2) doctor makes the decisions with patient’s input, 3) equally shared decision, 4) patient makes the decisions with doctor’s input, 5) patient makes the decisions. Caregiver-role CPS options were 1) doctor makes the decisions, 2) patient makes the decision with doctor, 3) patient and caregiver make the decisions with doctor, 4) caregiver makes the decisions with doctor. Matching responses of the dyads for each CPS question were considered concordant. We used descriptive statistics to summarize CPS for patients and caregivers and the concordance between them. We utilized logistic regression to assess dyads' sociodemographic information, patients' GA and physicians’ practice characteristics associated with patient-caregiver CPS concordance. Results: Enrolled dyads with completed CPS were included (N=332); mean age (SD) of patients and caregivers was 76.6 (5.3) and 66.6 (12.2). Women constituted 39% of patients and 76% of caregivers. Patient-role CPS for patients’ (and caregivers’) were 11% (6%) for doctor makes the decisions, 33% (28%) for doctor makes the decisions with patient’s input, 45% (49%) for equally shared, 9% (14%) for patient makes the decisions with doctor’s input, 2% (3%) for patient makes the decision. Patients’ (and caregivers’) answers on caregiver-role CPS were 20% (19%) for doctor makes the decisions, 18% (28%) for patient makes the decisions with doctor, 61% (52%) for patient and caregiver make the decisions with doctor and 1% (1%) for caregiver makes the decisions with doctor. Dyads concordance occurred in 46% of patient-role CPS and 54% of caregiver-role CPS, indicating moderate concordance. No baseline factors were associated in dyad concordance for either the patient-role or caregiver-role CPS. Conclusions: Clinicians should inquire about decisional control preferences of patients and caregivers in order to optimally support shared decision making. Clinical trial information: NCT02054741 .
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39

Parrish, Alan A. "Decisions, decisions." Nursing Standard 3, no. 34 (May 20, 1989): 36–37. http://dx.doi.org/10.7748/ns.3.34.36.s48.

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40

Steensma, David P. "Decisions, Decisions." Oncologist 14, no. 6 (May 27, 2009): 640–41. http://dx.doi.org/10.1634/theoncologist.2009-0081.

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Field, Ray. "Decisions decisions." Nursing Standard 13, no. 50 (September 1999): 63. http://dx.doi.org/10.7748/ns.13.50.63.s60.

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42

Du Toit, Andrea. "Decisions, decisions…" Nature Reviews Microbiology 20, no. 3 (December 20, 2021): 125. http://dx.doi.org/10.1038/s41579-021-00677-7.

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43

Tarran, Brian. "Decisions, decisions." Significance 15, no. 2 (April 2018): 1. http://dx.doi.org/10.1111/j.1740-9713.2018.01117.x.

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Jerger, James. "Decisions! Decisions!" Journal of the American Academy of Audiology 14, no. 10 (November 2003): i—ii. http://dx.doi.org/10.1055/s-0040-1715941.

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Piper, Adrian. "Decisions, Decisions." Grand Street, no. 60 (1997): 136. http://dx.doi.org/10.2307/25008166.

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Kast, Bas. "Decisions, decisions..." Nature 411, no. 6834 (May 2001): 126–28. http://dx.doi.org/10.1038/35075745.

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&NA;. "Decisions, Decisions..." PACEsetterS 5, no. 1 (January 2008): 24–25. http://dx.doi.org/10.1097/01.jbi.0000393345.64756.3f.

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Potter, Emma C., Karen A. Roberto, Nancy Brossoie, and Rosemary Blieszner. "Decisions, Decisions." Research on Aging 39, no. 4 (March 13, 2017): 476–500. http://dx.doi.org/10.1177/0164027516655581.

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Abstract:
African American families’ experiences with mild cognitive impairment (MCI) have received little attention in the research literature. Guided by the life-course perspective, we analyzed qualitative interview data from members of 27 African American families including the person with MCI (PwMCI), a relative or friend who was highly involved in the PwMCI’s daily life, and if available, a relative or friend who had at least monthly contact with the PwMCI. Findings uncovered variability in families’ MCI awareness, assessment, and need for role changes; the importance of reaching out to trusted others; and honoring PwMCI’s care preferences (e.g., who should provide care). Families held varying beliefs about engaging outside support; some families insisted on keeping all care within the family while others were open to the use of external services. We showcase how diagnosis acceptance and family decision-making are at the heart of how African American families respond to MCI.
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Kepecs, Adam. "Decisions, decisions..." Nature 458, no. 7240 (April 2009): 835. http://dx.doi.org/10.1038/458835a.

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Gannon, Frank. "Decisions, decisions." EMBO reports 7, no. 10 (August 2006): 953. http://dx.doi.org/10.1038/sj.embor.7400808.

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